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A comprehensive systematic literature review on intrusion detection systems
Effectively detecting intrusions in the computer networks still remains problematic. This is
because cyber attackers are changing packet contents to disguise the intrusion detection …
because cyber attackers are changing packet contents to disguise the intrusion detection …
On cloud security attacks: A taxonomy and intrusion detection and prevention as a service
Major provisioning of cloud computing is mainly delivered via Software as a Service,
Platform as a Service and Infrastructure as a Service. However, these service delivery …
Platform as a Service and Infrastructure as a Service. However, these service delivery …
Intelligent approach to build a Deep Neural Network based IDS for cloud environment using combination of machine learning algorithms
The appealing features of Cloud Computing continue to fuel its adoption and its integration
in many sectors such industry, governments, education and entertainment. Nevertheless …
in many sectors such industry, governments, education and entertainment. Nevertheless …
A survey of intrusion detection from the perspective of intrusion datasets and machine learning techniques
The evolution in the attack scenarios has been such that finding efficient and optimal
Network Intrusion Detection Systems (NIDS) with frequent updates has become a big …
Network Intrusion Detection Systems (NIDS) with frequent updates has become a big …
A fog computing based approach to DDoS mitigation in IIoT systems
Distributed denial of service (DDoS) cyber-attack poses a severe threat to the industrial
Internet of Things (IIoT) operation due to the security vulnerabilities resulted from increased …
Internet of Things (IIoT) operation due to the security vulnerabilities resulted from increased …
The rise of “malware”: Bibliometric analysis of malware study
Malicious software (malware) is a computer program designed to create harmful and
undesirable effects. It considered as one of the many dangerous threats for Internet users …
undesirable effects. It considered as one of the many dangerous threats for Internet users …
Daas: Dew computing as a service for intelligent intrusion detection in edge-of-things ecosystem
Edge of Things (EoT) enables the seamless transfer of services, storage, and data
processing from the cloud layer to edge devices in a large-scale distributed Internet of …
processing from the cloud layer to edge devices in a large-scale distributed Internet of …
An empirical study of using planning poker for user story estimation
NC Haugen - AGILE 2006 (AGILE'06), 2006 - ieeexplore.ieee.org
Group estimation of user stories is an important part of extreme programming (XP), used for
both planning releases and iterations. Research has shown that although group estimation …
both planning releases and iterations. Research has shown that although group estimation …
Adaptive machine learning‐based alarm reduction via edge computing for distributed intrusion detection systems
To protect assets and resources from being hacked, intrusion detection systems are widely
implemented in organizations around the world. However, false alarms are one challenging …
implemented in organizations around the world. However, false alarms are one challenging …
A fog-based privacy-preserving approach for distributed signature-based intrusion detection
Intrusion detection systems (IDSs) are the frontier of defense against transmissible cyber
threats that spread across distributed systems. Modern IDSs overcome the limitation of …
threats that spread across distributed systems. Modern IDSs overcome the limitation of …